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<p>In offshore wind turbine systems, irregular wave spectra, stochastic wind loading, and variable soil–structure interaction affects structural, electrical, and dynamic subsystems on different timescales. Our integrated multi-domain optimization technique synchronizes structural topology evolution, harmonic suppression, cross-domain state alignment, swarm-based coevolution, and digital-twin-driven robustness assessment. High-resolution metocean data, anisotropic marine-grade steel material characterization, and fast computational infrastructure for iterative simulation-based evaluation are assumed. These assumptions reflect North Sea deployment conditions, where turbulence reaches 15% and wave lengths vary widely. To evaluate design performance under multi-physics coupling, the framework maps material density to stress redistribution, links maritime loads to generator harmonic responses, and aligns structure motion and electrical stimulation frequencies. Neuro-fuzzy adaptability, swarm intelligence, and reinforcement-guided digital twin coherence monitoring iterate each subsystem. Within operational uncertainties, optimization enhances fatigue resistance, harmonic mitigation, material efficiency, and fault recovery. This integrated technology co-designs structural, electrical, and dynamic domains to stabilize offshore wind systems under different loads. The technology delivers robust turbine design across long operational horizons via cross-domain feedback and adaptive learning.</p>

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Swarm Intelligence-based Bioinspired Optimization Framework for Offshore Wind Turbine System With Digital Twin Validation

  • 期刊论文

  • 发表日期：

    2025年12月12日

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  • Xma R. Pote,
  • Sarala P. Adhau,
  • Vaibhaw R. Doifode,
  • Sarika D. Patil,
  • V. S. Rajguru,
  • Ramakant S. Ingole,
  • Tejas R. Patil,
  • Nischal Puri,
  • Niteen T. Kakade,
  • Aparna Gurjar,
  • Rohit Pawar,
  • Prashant T. Dhorabe,
  • Vikrant S. Vairagade

摘要

In offshore wind turbine systems, irregular wave spectra, stochastic wind loading, and variable soil–structure interaction affects structural, electrical, and dynamic subsystems on different timescales. Our integrated multi-domain optimization technique synchronizes structural topology evolution, harmonic suppression, cross-domain state alignment, swarm-based coevolution, and digital-twin-driven robustness assessment. High-resolution metocean data, anisotropic marine-grade steel material characterization, and fast computational infrastructure for iterative simulation-based evaluation are assumed. These assumptions reflect North Sea deployment conditions, where turbulence reaches 15% and wave lengths vary widely. To evaluate design performance under multi-physics coupling, the framework maps material density to stress redistribution, links maritime loads to generator harmonic responses, and aligns structure motion and electrical stimulation frequencies. Neuro-fuzzy adaptability, swarm intelligence, and reinforcement-guided digital twin coherence monitoring iterate each subsystem. Within operational uncertainties, optimization enhances fatigue resistance, harmonic mitigation, material efficiency, and fault recovery. This integrated technology co-designs structural, electrical, and dynamic domains to stabilize offshore wind systems under different loads. The technology delivers robust turbine design across long operational horizons via cross-domain feedback and adaptive learning.